About Job/Role

The AI/ML Engineer – Generative AI & RAG will be responsible for designing, developing, and deploying state-of-the-art machine learning models with a focus on Generative AI and Retrieval-Augmented Generation (RAG).
The role involves building scalable solutions using Python, large language models (LLMs), and retrieval pipelines to solve complex business problems and enhance product capabilities.

Roles and Responsibilities

Design, develop, and deploy scalable ML solutions using LLMs and RAG architecture
Implement and optimize prompt engineering, embeddings, vector databases, and retrieval mechanisms
Develop APIs and services to integrate AI solutions into production systems
Collaborate with data engineers, product managers, and other stakeholders to define technical requirements
Continuously evaluate and improve model performance and accuracy
Stay updated with the latest research and developments in GenAI, NLP, and ML
Contribute to technical documentation, code reviews, and best practices
Ensure all AI solutions comply with ethical and data privacy standards

Required Qualification

Bachelor's or Master’s degree in Computer Science, AI, Data Science, or related field
Strong programming skills in Python, including use of libraries like TensorFlow, PyTorch, Hugging Face Transformers, LangChain, etc.
Experience with LLMs (GPT, LLaMA, Claude, etc.) and RAG framework.
Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate)
Solid understanding of NLP, embeddings, tokenization, and attention mechanisms
Familiarity with APIs, RESTful services, and cloud deployment (AWS/GCP/Azure)
Strong foundation in data structures, algorithms, and ML workflows

Preferred Qualifications

Soft Skills

Key Relationships

Role Dimensions

Success Measures (KPIs)

Competency Framework Alignment

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